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Research Briefs in Economic Policy No. 65

Ban the Box, Criminal Records, and Statistical Discrimination

By
Amanda Agan and Sonja Starr

December 7, 2016

In recent years, many cities and states have passed
“Ban-the-Box” (BTB) laws, which seek to expand access
to employment for people with criminal records. These laws ban
employers from including questions about criminal records on job
applications or in interviews. Employers are still permitted to
conduct background checks, but not until the end of the hiring
process. The theory is that once hiring managers have met the
applicants in person, they will be more likely to consider
carefully whether a conviction is job-relevant, rather than
categorically dismissing applicants with records. Many advocates of
BTB have framed it as a tool for reducing racial disparity in
employment, and especially for reducing high rates of unemployment
among black men. The rationale is straightforward: black men have
higher felony conviction rates and thus should benefit
disproportionately from policies that open doors to people with
such convictions.

However, there is a theoretical reason to worry that this
approach could backfire. Economists have long predicted that when
employers are deprived of individualized information about job
applicants they will engage in “statistical
discrimination”: that is, they will rely on other observable
characteristics to make (accurate or inaccurate) group-based
generalizations about an applicant. In the BTB context, employers
might use the race of the applicant to guess at the likelihood the
applicant has a criminal record: they may simply assume that black
male applicants are likely to have them, while white applicants are
not. In short, employers who cannot discriminate directly based on
criminal records might, instead, discriminate based on race. Doing
so would be unlawful, of course, but laws against racial
discrimination in hiring have proven difficult to enforce.

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To investigate the potential for statistical discrimination
after BTB, we submitted nearly 15,000 applications on behalf of
fictitious applicants before and after BTB laws went into effect.
Our study focused on New Jersey and New York City, both of which
implemented BTB laws for private employers in 2015. We randomly
varied the race of the applicant (black or white) and whether the
applicant had a felony conviction; otherwise, applicants’
characteristics were similar and randomized. Because our pools of
white and black applicants thus had identical sets of other traits,
we can confidently attribute systematic differences in white and
black callback rates to racial discrimination. Likewise, because
our applicants with and without criminal records were otherwise
identical, we can confidently conclude that any pre-BTB differences
in their callback rates were due to those records. Our
field-experimental design thus has an advantage over real-world
observational approaches, in which causal inferences can be
confounded by other differences in applicant pools.

Our results pose a potential dilemma for policymakers: they
support BTB’s basic premise that criminal records are a major
barrier to employment access, but they also support the concern
about statistical discrimination. When employers asked about
criminal convictions, applicants without a felony conviction were
63 percent more likely to be called back than those with a
conviction (5.2 percentage points over a baseline of 8.2 percent).
This effect essentially disappeared after the enactment of the BTB
law because almost all employers complied by removing the
criminal-record question from their applications. Our study tested
only initial callbacks, so we could not evaluate BTB’s
additional premise that getting a foot in the door would help
applicants with records get jobs even though employers eventually
conduct background checks. However, our results do suggest that BTB
is effective at helping applicants with records to obtain job
interviews.

However, we also found that BTB substantially increases racial
discrimination in employer callbacks. At companies that asked about
criminal records before BTB, white applicants received 7 percent
more callbacks than similar black applicants; after BTB, this gap
grew to 45 percent. (In percentage point terms, we found that BTB
expanded the black-white gap by about 4 percentage points: a large
increase, given that the overall callback rate for the sample was
just under 12 percent.) In contrast, we did not see any
significant change at companies that did not ask about criminal
records before BTB went into effect and were thus unaffected by
BTB, and if anything, the black-white gap shrank at those companies
over the same period. This provides reason to believe that the
large expansion in the black-white gap at affected companies was a
casual effect of BTB, rather than an unrelated change that happened
to occur over the same time period.

The growth in the black-white gap appears to come from a
combination of losses to black applicants and gains to white
applicants. In particular, black applicants without
criminal records see a substantial drop in callback rates after
BTB, while white applicants with criminal records see
large gains. This pattern supports the statistical discrimination
theory: when employers lack criminal record information, they tend
to assume that black applicants (and not white applicants) are
likely to have records. Thus, the gains that BTB offers to people
with records (in particular, white people with records) may come at
the cost of black applicants without records, who lose their
ability to neutralize employers’ negative assumptions by
conveying their clean records. Further analysis suggests that these
assumptions are exaggerated relative to the actual distribution of
felony convictions in the population: that is, employers may be
relying on assumptions or stereotypes about black criminality that
are statistically ill-founded.

We believe our findings suggest a complicated challenge for
policymaking. Of course, BTB’s implications for racial
discrimination are not the only relevant consideration.
Policymakers might decide that because of the especially serious
employment barriers people with criminal records face, expanding
job access for them is important enough to be worth pursuing
despite the unintended consequence of reduced opportunities for
black men without records. Alternatively, they might seek to pair
BTB with strategies that attempt either to improve enforcement of
racial discrimination prohibitions (a difficult task historically)
or to change employers’ underlying incentives vis-à-vis
people with records (for example, by expanding tax credits for
hiring them). What we think is clear is that BTB, at least taken
alone, should not be seen as a strategy for reducing racial
disparity in employment: with respect to that goal, our study finds
that it is counterproductive.

Note:

This research brief is based on Amanda Agan and Sonja Starr,
“Ban the Box, Criminal Records, and Statistical
Discrimination: A Field Experiment,” University of Michigan
Law and Economics Research Paper no. 16-012, June 14, 2016,